by opportunity [9]. Based on this kind of phenomena as well as
others one may readily conclude that besides genome other factors
such as congenial soil (microenvironment) and inflammation also
play key roles in cancer genesis and progression and these factors
cannot be ignored.
From both the clinic and theoretical sides, evidences also sug-
gest that the genetic and genomic information are important but
not enough. Biological systems are characterized by the stochastic
dynamical phenomena and concepts such as adaptation [10, 11],
robustness [12, 13],phenotype switch [14, 15]. In tumors such
concepts correspond to well-documented drug resistance [16],
tremendously difficult for cancer regression [17] and genesis and
progression to tumor from normal tissue respectively. The phe-
nomena and concepts arise from the complex regulatory machin-
ery, the building blocks of the regulatory machinery including
genetic switch, feedback loops [18], double-edge effect [19, 20],
etc. A desirable method to make the biological system’s phenome-
non and concepts clear is to understand and manipulate the regu-
latory machinery quantitatively, it is also one of the biggest
challenges for contemporary biology [21–25]. It is clear that we
cannot achieve this goal just by using genetic information. Consen-
sus starts to form that complete information of the DNA sequence
of an organism will not enable us to reconstruct the regulatory
machinery quantitatively because of the many gaps between the
genotype and the phenotype. We need to reveal the regulatory
machinery behind a biological phenomenon quantitatively, which
would be of great importance for our understanding and manip-
ulating biological phenomenon, such as cancer genesis and
progression.
To meet this challenge, based on the current understanding of
biological systems, the endogenous molecular-cellular network
hypothesis for cancer genesis and progression has been proposed
[26–28]. In the following section, the key aspects of the hypothe-
sized theory and its implications will be reviewed and elaborated. In
Subheading2.1, we will discuss the basic elements in the hypothesis
and the essential requirements. In Subheading2.2, we applied the
endogenous molecular-cellular network hypothesis in hepatocellu-
lar carcinoma (HCC). In Subheading2.3 and 2.4, We use the
endogenous molecular-cellular network hypothesis to quantify
and understand the genesis and progression of HCC, which sug-
gest that the stable states of the endogenous network can be used to
represent normal liver and HCC at both the modular and molecular
levels. In Subheading2.5, we explored a genetic mutation pattern
in cancer using the endogenous network hypothesis. In Subhead-
ing2.6, we explored potential strategies to cure or relieve HCC.
The similarities and differences among similar proposals, along with
a few dominant cancer theories, are discussed in Subheading3.We
Endogenous Molecular-Cellular Network Cancer Theory 217